Five influential women in data science
There’s a long history of gender inequality in science. Katherine Johnson and Cristine Darden are just two of many scientists who made valuable contributions to NASA. Their stories remained lost to the world, until journalist Margot Lee Shetterly’s book Hidden Figures: The American Dream and the Untold Story of the Black Women Who Helped Win the Space Race, and the subsequent film celebrated them.
In Invisible Women: Exposing Data Bias in a World Designed for Men, author Carolina Criado Perez explore the impact of gender gaps in data on public health policies, disaster relief, international policies, politics and more. She says, “Brilliance bias is in no small part a result of a data gap: we have written so many female geniuses out of history, they just don’t come to mind as easily.”
The world will be a better place with more women in data science. When we include more women in all spheres of life, it’s better for everyone. Women’s impact on civil society, academia and decision-making is profound. The future holds hope because many inspiring women in STEM are doing fantastic work. We’re celebrating five influential women in data science, actively driving change.
Dr. Hima Lakkaraju
Dr Lakkaraju focuses her research on trustworthy machine learning. She has developed tools to make previously “black box” models more explainable. Her methods are used to make fair and interpretable models that help people make high-stakes decisions. For example, her work has been used by judges in New York City as they attempt to use models to make decisions about whether or not to release defendants on bail. She is an Assistant Professor at Harvard University with appointments in the Business School and the Department of Computer Science. Vanity Fair named her one of the innovators to watch, and MIT Tech Review named her one of the 35 innovators under 35.
Dr Rachel Thomas co-founded fast.ai, a company with a mission to bring deep learning to the people. Fast.ai writes high-level software to make deep learning more accessible, and it provides free courses in deep learning to anyone in the world. When she is not developing the most widely-used deep learning course globally, Dr Thomas also researches algorithmic bias and data ethics and is the Professor of Practice at the Queensland University of Technology Centre for Data Science. In 2017, Forbes selected her as one of 20 Incredible Women in AI.
Dr Joy Buolamwini
Dr Joy Buolamwini wins hands down for having the coolest job title as the Founder of the Algorithmic Justice League. Described by Fortune Magazine as the “conscience of the AI Revolution”, Dr Buolamwini first encountered bias in facial recognition systems when she had to wear a white mask for the software to detect her face. She is a digital activist and a ‘poet of code’ who takes on large tech companies and the US government. She asks them to question if the benefits outweigh the harm with machine learning systems and examine who the systems are failing. Dr Buolamwini is an AI Researcher at MIT Media Lab.
Dr Tarin Claunwat
Dr Tarin Clanuwat comes to AI from an unexpected place, a PhD in Classical Japanese Literature. Dr Clanuwat wanted to make historical texts accessible to the general public. But, most Japanese people cannot read Kuzushiji characters. So, she began to use deep learning to build a model that would transcribe the characters into modern Japanese characters. Her software is now available as an app! She wants to encourage more humanities researchers to use machine learning in their research so that they can take advantage of the vast amounts of data in their fields. Dr Clanuwat works as a senior research scientist at Google Brain, Tokyo.